1. Field of the Invention
The invention relates generally to the field of compressed or encoded digital audio signals and more particularly to audio compression that uses scale factors or floating point representation to represent audio signals.
2. Description of the Related Art
A number of methods of coding and decoding digital signals are known, and are typically employed either to decrease the bit requirements for transmission and storage, or to increase the perceived quality of audio playback (subject to a bitrate constraint). For example, some such as DTS coherent acoustics (see U.S. Pat. No. 5,974,380) and Dolby AC3 are in common commercial use, as are numerous variants of MPEG-2 compression and decompression.
In any digital audio representation, the signal is periodically sampled, then the series of samples are quantized by some method to represent an audio signal. In many codecs (encoder/decoder systems), the signal is represented by a series of quantized samples organized as a temporal sequence (time domain representation). In other codecs, the samples may be mathematically transformed by any of a number of mathematical methods, to yield a “frequency domain” representation, also called a spectral representation or a transform representation. Such codecs are often referred to a “transform codecs”.
Whether the encoded representation uses time domain samples, encoded spectral values, or some other transformed series of data, it is often found advantageous to adapt the numerical representation of the samples to more efficiently use the available bits. It is known to represent data by using scale factors. Each data value is represented by a scale factor and a quantity parameter which is understood to be multiplied by the scale factor to recover the original data value. This method is sometimes referred to as a “scaled representation”, sometimes specifically a block-scaled representation, or sometimes as a “floating-point” representation. It should be apparent that floating point representation is a special case of a scaled representation, in which a number is represented by the combination of a mantissa and exponent. The mantissa corresponds to the quantity parameter; the exponent to a scale factor. Typically the scale factor bits may be represented in some non-linear scheme, such as an exponential or logarithmic mapping. Thus, each quantization step of the scale factor field may represent some number of decibels in a log base 10 scheme (for example).
Although the use of scale factors commonly reducing the bit rate requirement for transmission, in a “forward-adaptive” codec it is required to transmit the scale factors in some manner. At lower bit rates the transmission of the scale factors requires a significant portion of the overall bit rate. Thus it is desirable to reduce the number of bits required to transmit the scale factors. The most common prior approach to this problem is to transmit a single scale factor associated with some larger plurality (block) of samples. One variant of this technique is referred to as “block-floating point.” This method strikes a compromise between optimal quantization and the need to reduce the bits required for transmission of scale factors. The success of the technique is largely dependent on the time and frequency behavior of the signal, and signal transients present challenges.